1 citations · 2 across the 4 of their papers we have counts for
4 papers
Selective Mixup Fine-Tuning for Optimizing Non-Decomposable Objectives
Shrinivas Ramasubramanian, Harsh Rangwani, Sho Takemori +3
The rise in internet usage has led to the generation of massive amounts of data, resulting in the adoption of various supervised and semi-supervised machine learning algorithms, wh…
Towards Accurate Quantum Chemical Calculations on Noisy Quantum Computers
Naoki Iijima, Satoshi Imamura, Mikio Morita +4
Variational quantum eigensolver (VQE) is a hybrid quantum-classical algorithm designed for noisy intermediate-scale quantum (NISQ) computers. It is promising for quantum chemical c…
Cost-Sensitive Self-Training for Optimizing Non-Decomposable Metrics
Harsh Rangwani, Shrinivas Ramasubramanian, Sho Takemori +3
Self-training based semi-supervised learning algorithms have enabled the learning of highly accurate deep neural networks, using only a fraction of labeled data. However, the major…
On theta series attached to the Leech lattice
Shoyu Nagaoka, Sho Takemori
Some congruence relations satisfied by the theta series associated with the Leech lattice are given.